How Airbnb’s data engineers and analytics engineers built a consistent and flexible data modeling framework to support the expansion into Homes, Experiences, and Services. By : Patrick Lam , Namrata Lamba , Jamie Stober With the May 2025 Summer Release, Airbnb redesigned its app, relaunched Experiences, and debuted Services, pushing us beyond our traditional Homes focus. For the data teams,…
Airbnb
https://medium.com/airbnb-engineering · 10 posts · history since 2026 · active
9 Jun
4 Jun
How Airbnb built a Kubernetes sidecar to deliver dynamic configuration reliably at scale. By : Bo Teng , Cosmo Qiu , Siyuan Zhou , Ankur Soni , Xin Huang , Willis Harvey Introduction In our previous post , we explored Airbnb’s dynamic configuration system, Sitar, with a focus on service architecture and configuration change safety. Now for the harder question:…
2 Jun
How Airbnb used sequential geographic recovery signals and prior propagation to generate reliable corridor-level forecasts when local data was scarce. By: Harrison Katz The problem with unprecedented shocks Almost every forecasting system is built on the same implicit assumption: the future will resemble the past. You train on historical data, you validate on holdout periods, and you trust that past…
19 May
How Airbnb shifts from PaaS to an internal knowledge graph infrastructure at scale. By: Lucen Zhao , Shukun Yang , Ashish Jain Knowledge graphs offer a natural and powerful way to represent relationships between entities. Many real-world systems are fundamentally about connections. Airbnb’s identity graph captures relationships between users in a graph database. The identity graph serves aggregated insights that…
13 May
Moving from an internal tool to a community-driven, production-ready data mesh. By : Ryan Tanner , Raymie Stata , Adam Miskiewicz Introduction We’re excited to announce the 1.0 release of the Viaduct. This release marks a shift from Viaduct being an Airbnb-internal tool that happens to be open source to a true community-driven project with a stable public API. The…
5 May
Designing monitoring that works when everything else doesn’t. By : Abdurrahman J. Allawala Introduction When an incident hits, teams lean on observability to answer the only questions that matter: what’s broken, and why? Monitoring systems are designed to help you answer these questions, and they usually do. But what happens when your observability stack is dependent on the same systems…
28 Apr
How Airbnb built a lightweight workflow engine to solve durable execution. By : Ricardo Gamba , Andriy Sergiyenko Introduction: The durable execution problem Picture this hypothetical flow: A host submits an insurance claim about their listing to Airbnb. The system needs to validate the claim, run trust and safety checks, assess estimates, process the payout, and send notifications. Halfway through…
21 Apr
How we built a storage system that ingests 50 million samples per second and stores 2.5 petabytes of logical time series data. By : Rishabh Kumar Modern observability practice encourages instrumenting every meaningful code path. Over the past 15 years, open-source observability SDKs like Prometheus, OpenTelemetry, and StatsD have made deep instrumentation nearly ubiquitous. These days, most software — open-source…
14 Apr
Discover how Airbnb prioritizes user privacy while building a more connected community, empowering guests to engage socially, connect confidently, and maintain control of their personal data. By: Joy Jing ✨ Building a more connected community At Airbnb, our hosts and guests form the heart of our community. As shared by CEO Brian Chesky , we’re evolving into a more social…
7 Apr
A production-tested approach for moving a large-scale metrics pipeline from StatsD to OpenTelemetry and Prometheus. By: Eugene Ma , Natasha Aleksandrova When migrating to a new monitoring system, you’ll want to frontload the work to collect all your metrics. This exposes bottlenecks at full write scale and unblocks the migration of assets which require real data for validation, such as…